Instructions to use MelissaJ/myLucia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MelissaJ/myLucia with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="MelissaJ/myLucia")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MelissaJ/myLucia", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Model Card for VITS Model
Model Description
This model is a Variational Inference Text-to-Speech (VITS) model trained on Korean datasets.
Usage
To use this model with the Huggingface Inference API, follow the steps below:
Inference API
from transformers import pipeline
tts = pipeline(model="path_to_your_model")
output = tts("์๋
ํ์ธ์")
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